Zayet, Tasnim M. A. and Ismail, Maizatul Akmar and Varathan, Kasturi Dewi (2024) Aspect Extraction in Domain Lexicon Generation: A New Frequency-Based Approach. IEEE Access, 12. pp. 138972-138984. ISSN 2169-3536, DOI https://doi.org/10.1109/ACCESS.2024.3442930.
Full text not available from this repository.Abstract
Domain sentimental lexicon building become an attractive field in recent years. This is due to the increased number of users' generated data through the internet besides the different sentiments of opinion words in different contexts. Domain lexicons mainly consist of opinion pairs and their associated sentiment. Any opinion pair is formed by a domain word and one of its associated opinion words. Therefore, to generate a domain lexicon from a domain corpus, domain word extraction is needed with their associated opinion words. One of the traditional approaches is frequency-based approaches. However, the ambiguity problem is a big concern of these approaches. This paper introduced a frequency-based equation that considers the context of the words for domain word extraction. The equation was tested on five Amazon reviews datasets and it proved its efficiency over other used frequency-based equations in terms of recall and precision. Therefore, more related lexicons to the domains were generated.
| Item Type: | Article |
|---|---|
| Funders: | Universiti Malaya (UM) International Collaboration (ST005-2023) |
| Uncontrolled Keywords: | Feature extraction; Data mining; Frequency-domain analysis; Social networking (online); Sentiment analysis; Semantics; Accuracy; Statistical analysis; Text processing; Text mining; Aspect; domain lexicon; frequency-based; sentiment analysis; statistical; word extraction; context |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Divisions: | Faculty of Computer Science & Information Technology > Department of Information System |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 28 Nov 2024 05:23 |
| Last Modified: | 28 Nov 2024 05:23 |
| URI: | http://eprints.um.edu.my/id/eprint/47132 |
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